Search form

News

Study shows playing high school football changes the teenage brain

A research study led by EE Prof. Chunlei Liu (senior author) and postdoc Nan-Ji Gong (first author), which is the cover story of the November issue of Neurobiology of Disease, found that a single season of high school football may be enough to cause microscopic changes in the structure of the brain. The team (which included researchers from Duke and UNC Chapel Hill) used a new type of magnetic resonance imaging (MRI) to take brain scans of 16 high school players, ages 15 to 17, before and after a season of football. They found significant changes in the structure of the grey matter in the front and rear of the brain, where impacts are most likely to occur, as well as changes to structures deep inside the brain. This is one of the first studies to look at how impact sports affect the brains of children at this critical age.

EE Prof. and Dean of Engineering Tsu-Jae King Liu as been elected to the 2019 Silicon Valley Engineering Council (SVEC) Hall of Fame. Inductees must have demonstrated significant engineering or technical achievements, provided significant guidance in new and developing fields of engineering-based technology, and/or have managed or directed an organization making noteworthy contributions in design, manufacturing, production, or service through the uses of engineering principles and applications. They also must have contributed significantly to one or more technical societies and accomplished significant community service activities (or have provided noteworthy advice to governmental committees, etc.). King Liu is known for her contributions to nanoscale MOS transistors, memory devices, and MEMS devices. Other EECS inductees include Profs. Randy Katz (2018), Chenming Hu (2017), Paul Gray (2015), David Hodges (2012), and David Patterson (2005).

Skin-like sensor maps blood-oxygen levels anywhere in the body

A new flexible sensor developed by Berkeley EE researchers can map blood-oxygen levels over large areas of skin, tissue and organs, potentially giving doctors a new way to monitor healing wounds in real time. The research group, which includes Prof. Ana Claudia Arias, Yasser Khan, Donggeon Han, Adrien Pierre, Jonathan Ting, Xingchun Wang and Claire Lochner (plus researchers from Cambridge Display Technology Ltd), have created a lightweight, thin, and flexible oximeter made of organic electronics printed on bendable plastic that molds to the contours of the body. The sensor, which is described in this week's Proceedings of the National Academy of Sciences, is made of an alternating array of printed light-emitting diodes and photodetectors and can detect blood-oxygen levels anywhere it is placed. The sensor shines red and infrared light into the skin and detects the ratio of light that is reflected back.

Ming Wu to step down as faculty director of the NanoLab

EE Prof. Ming Wu will be stepping down as faculty director of the Berkeley Marvell Nanofabrication Laboratory (NanoLab) at the end of 2018. He took up the position in 2008 after his predecessor, EE Prof. Tsu-Jae King Liu, became associate dean of research at the College of Engineering. At the time, a new state-of-the-art clean room research facility was in its final stages of construction in Sutardja Dai Hall. Under Wu’s leadership, multiple capabilities were added to the NanoLab – including a suite of high-resolution spectroscopy and microscopy tools.

UC Berkeley computer theorists led by CS Prof. Umesh Vazirani, published a proof of random circuit sampling (RCS) as a verification method to prove quantum supremacy in a paper published Monday, Oct. 29, in the journal Nature Physics. Quantum supremacy is the term that describes a quantum computer’s ability to solve a computational task that would be prohibitively difficult for any classical algorithm. “Besides being a milestone on the way to useful quantum computers, quantum supremacy is a new kind of physics experiment to test quantum mechanics in a new regime. The basic question that must be answered for any such experiment is how confident can we be that the observed behavior is truly quantum and could not have been replicated by classical means. That is what our results address,” said Vazirani.

IP paper wins 2018 ACM SenSys Test of Time Award

A paper written by CS Prof. David Culler and alumnus Jonathan Hui (M.S. '05/Ph.D. '08) in 2008 titled "IP is Dead, Long Live IP for Wireless Sensor Networks" has won the Association of Computing Machinery (ACM) Conference on Embedded Networked Sensor Systems (SenSys) 2018 Test of Time Award. The paper dispelled the notion that IP cannot run on wireless embedded sensors and made a long term impact on standards like 6LoWPAN and platforms like Thread. The award recognizes papers that are at least 10 years old and have had long lasting impact on networked embedded sensing system science and engineering. Culler previously won this award in both 2014 and 2015.

A paper titled “Graphical Lasso and Thresholding: Equivalence and Closed-form Solutions” by IEOR PhD candidate Salar Fattahi and EE Assistant Prof. Somayeh Sojoudi has won the 2018 Institute for Operations Research and the Management Sciences (INFORMS) Data Mining (DM) Best Paper Award. The paper compares the computationally-heavy Graphical Lasso (GL) technique, a popular method for learning the structure of an undirected graphical model, with a numerically-cheap heuristic method that is based on simply thresholding the sample covariance matrix. By analyzing the properties of this conic optimization problem, the paper shows that its true complexity is indeed linear (both in time and in memory) for sparse graphical models and solves instance as large as 80,000×80,000 (more than 3.2 billion variables) in less than 30 minutes on a standard laptop computer, while other state-of-the-art methods do not converge within 4 hours. The award recognizes excellence among DM members, particularly its student members, and was announced at the INFORMS Annual Meeting in Phoenix, Arizona, on November 5th.

In the Age of A.I., Is Seeing Still Believing?

EE Profs. Hany Farid and Alyosha Efros, the class CS 194-26—Image Manipulation and Computational Photography, and grad students Shiry Ginosar, Deepak Pathak, Angjoo Kanazawa, Richard Zhang, Jacob Huh and Tinghui Zhou are profiled in a New Yorker article titled "In the Age of A.I., Is Seeing Still Believing?" about how advances in digital imagery could deepen the fake-news crisis—or help us get out of it. Farid is an expert in photo-forensics who "trained" a neural network to pick out numbers in the pixels of a degraded image of a license plate. Efros pioneered a method for intelligently sampling bits of an image and probabilistically recombining them so that a texture could be indefinitely and organically extended (known in Photoshop as "content-aware fill"). True realism, Efros said, requires “data, data, data” about “the gunk, the dirt, the complexity of the world,” which is best gathered by accident, through the recording of ordinary life.

EE Prof. Alberto Sangiovanni-Vincentelli has won the 2018 Association of Computing Machinery (ACM) Special Interest Group on Design Automation (SIGDA) Pioneering Achievement Award. This award honors a person for a lifetime of outstanding contributions within the scope of electronic design automation, as evidenced by ideas pioneered in publications, industrial products, or other relevant contributions. The award is based on the impact of the contributions throughout the nominee’s lifetime. Sangiovanni-Vincentelli is known for his contributions to cyber-physical systems and design automation. He co-founded two companies in the field: Cadence Design Systems and Synopsys, Inc.

Machine Learning to Help Optimize Traffic and Reduce Pollution

CS Prof. Alexandre Bayen, the director of the Institute of Transportation Studies, is leading a traffic-smoothing project dubbed CIRCLES (Congestion Impact Reduction via CAV-in-the-loop Lagrangian Energy Smoothing) that applies deep reinforcement learning to self-driving cars to smooth traffic, reduce fuel consumption, and improve air quality. The potential for cities is enormous,” said Bayen. “Experiments have shown that the energy savings with just a small percentage of vehicles on the road being autonomous can be huge. And we can improve it even further with our algorithms.”